Ground plane detection is an important pre-processing step in the field of embedded vision. In advanced driver assistance systems (ADAS), ground plane detection operations provide information for location of a road plane in an image. This information may be used in various ADAS applications such as obstacle and vehicle detection.
Various approaches exist for ground plane detection including use of stereo images, use of homography and texture-based segmentation. However, each of these approaches has drawbacks. There is a need for an improved method for ground plane detection, particularly one that could be used in ADAS.